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Gait alterations in those with mild unilateral knee pain during walking may provide clues to modifiable alterations that affect progression of knee pain and osteoarthritis (OA). To examine this, we applied machine learning (ML) approaches to gait data from wearable sensors in a large observational knee OA cohort, the Multicenter Osteoarthritis (MOST) study. Participants completed a 20-m walk test wearing sensors on their trunk and ankles. Parameters describing spatiotemporal features of gait and symmetry, variability and complexity were extracted. We used an ensemble ML technique (“super learning”) to identify gait variables in our cross-sectional data associated with the presence/absence of unilateral knee pain. We then used logistic regression to determine the association of selected gait variables with odds of mild knee pain. Of 2066 participants (mean age 63.6 [SD: 10.4] years, 56% female), 21.3% had mild unilateral pain while walking. Gait parameters selected in the ML process as influential included step regularity, sample entropy, gait speed, and amplitude dominant frequency, among others. In adjusted cross-sectional analyses, lower levels of step regularity (i.e., greater gait variability) and lower sample entropy(i.e., lower gait complexity) were associated with increased likelihood of unilateral mild pain while walking [aOR 0.80 (0.64–1.00) and aOR 0.79 (0.66–0.95), respectively].

Aims/hypothesis Our aim was to assess the association of perceived racism with type 2 diabetes, and the possible mediating influence of diet and BMI. Methods The Black Women’s Health Study, a follow-up of 59,000 African-American women, began in 1995. Over 16 years 5344 incident cases of diabetes occurred during 576,577 person-years. Cox proportional hazards models were used to estimated HRs and 95% CIs for categories of ‘everyday racism’ (interpersonal racism in daily life) and ‘lifetime racism’ (reporting ever treated unfairly due to race with respect to police, housing or work) and incident type 2 diabetes. Models were adjusted for age, questionnaire cycle, marital status, socioeconomic status, education, family history of diabetes, physical activity, alcohol use and smoking status, with and without inclusion of terms for dietary patterns and adult BMI. Results Compared with women in the lowest quartile of exposure, women in the highest quartile of exposure to everyday racism had a 31% increased risk of diabetes (HR 1.31; 95% CI 1.20, 1.42) and women with the highest exposure to lifetime racism had a 16% increased risk (HR 1.16; 95% CI 1.05, 1.27). Mediation analysis estimated that BMI accounted for half of the association between either the everyday or lifetime racism measure and incident diabetes. Conclusions/interpretation Perceived everyday and lifetime racism were associated with increased risk of type 2 diabetes in this cohort of African-American women and appear to be at least partly mediated by BMI.

The world is currently in a pandemic of COVID-19 (Coronavirus disease-2019) caused by a novel positive-sense, single-stranded RNA β-coronavirus referred to as SARS-CoV-2. Here we investigated rates of SARS-CoV-2 infection in the greater Cincinnati, Ohio, USA metropolitan area from August 13 to December 8, 2020, just prior to initiation of the national vaccination program. Examination of 9,550 adult blood donor volunteers for serum IgG antibody positivity against the SARS-CoV-2 Spike protein showed an overall prevalence of 8.40%, measured as 7.56% in the first 58 days and 9.24% in the last 58 days, and 12.86% in December 2020, which we extrapolated to ~20% as of March, 2021. Males and females showed similar rates of past infection, and rates among Hispanic or Latinos, African Americans and Whites were also investigated. Donors under 30 years of age had the highest rates of past infection, while those over 60 had the lowest. Geographic analysis showed higher rates of infectivity on the West side of Cincinnati compared with the East side (split by I-75) and the lowest rates in the adjoining region of Kentucky (across the Ohio river). These results in regional seroprevalence will help inform efforts to best achieve herd immunity in conjunction with the national vaccination campaign.

Background Germ Defence ( www.germdefence.org ) is an evidence-based interactive website that promotes behaviour change for infection control within households. To maximise the potential of Germ Defence to effectively reduce the spread of COVID-19, the intervention needed to be implemented at scale rapidly. Methods With NHS England approval, we conducted an efficient two-arm (1:1 ratio) cluster randomised controlled trial (RCT) to examine the effectiveness of randomising implementation of Germ Defence via general practitioner (GP) practices across England, UK, compared with usual care to disseminate Germ Defence to patients. GP practices randomised to the intervention arm ( n  = 3292) were emailed and asked to disseminate Germ Defence to all adult patients via mobile phone text, email or social media. Usual care arm GP practices ( n  = 3287) maintained standard management for the 4-month trial period and then asked to share Germ Defence with their adult patients. The primary outcome was the rate of GP presentations for respiratory tract infections (RTI) per patient. Secondary outcomes comprised rates of acute RTIs, confirmed COVID-19 diagnoses and suspected COVID-19 diagnoses, COVID-19 symptoms, gastrointestinal infection diagnoses, antibiotic usage and hospital admissions. The impact of the intervention on outcome rates was assessed using negative binomial regression modelling within the OpenSAFELY platform. The uptake of the intervention by GP practice and by patients was measured via website analytics. Results Germ Defence was used 310,731 times. The average website satisfaction score was 7.52 (0–10 not at all to very satisfied, N  = 9933). There was no evidence of a difference in the rate of RTIs between intervention and control practices (rate ratio (RR) 1.01, 95% CI 0.96, 1.06, p  = 0.70). This was similar to all other eight health outcomes. Patient engagement within intervention arm practices ranged from 0 to 48% of a practice list. Conclusions While the RCT did not demonstrate a difference in health outcomes, we demonstrated that rapid large-scale implementation of a digital behavioural intervention is possible and can be evaluated with a novel efficient prospective RCT methodology analysing routinely collected patient data entirely within a trusted research environment. Trial registration This trial was registered in the ISRCTN registry (14602359) on 12 August 2020.

Profound degeneration of dopamine (DA) neurons and reduced DA levels in the brain is recognized as an underlying cause of Parkinson's Disease (PD). The standard treatment for PD is levodopa (L-DOPA), but its effectiveness wanes over time and prolonged usage can lead to L-DOPA-induced-dyskinesia (LID). An adeno-associated virus (AAV)-based strategy to overexpress aromatic l-amino acid decarboxylase (AADC) in the striatum combined with L-DOPA therapy shows promise for symptomatic improvement but requires an invasive delivery approach. Here, we generated enhancer AAVs to drive AADC expression in key cell types and paired them with a blood-brain barrier (BBB)-penetrant capsid. We characterized the AAVs in mouse following multiple routes of administration and found that cell-type specific viral treatment ameliorated motor deficits and LID in PD disease models. This cell type-specific viral rescue strategy showed similar or better phenotypic rescue compared to a ubiquitous targeting approach and improved mortality. Additionally, we characterized the expression of an AAV-AADC vector capable of mouse phenotypic rescue in non-human primate (NHP) following two routes of administration. This novel therapeutic strategy in combination with L-DOPA may enable a less invasive and better tolerated approach to treat motor deficits in PD patients.Competing Interest StatementThe authors have declared no competing interest.